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ِdr Shahnaz Khademizadeh, Mrs Fatemeh Rafieinasab, Dr Natarajan Radhakrishnan,
Volume 11, Issue 1 (6-2024)
Volume 11, Issue 1 (6-2024)
Abstract
Introduction
With the emergence of the Internet and the expansion of information technologies in the current era, along with the increase in awareness and literacy levels in human societies, there has been a growing interest in accessing information in various fields. One type of information that has always captivated the general public is health-related information, as it directly impacts their quality of life. Health information encompasses a wide range of data that can influence decisions related to individual and social well-being. Electronic health resources play a crucial role in helping individuals manage important health issues, make informed decisions about their health, and communicate with healthcare providers. Studies have shown that internet users not only exhibit better adherence to treatment, reduced anxiety, and a greater sense of security, but also demonstrate improved self-care behaviors compared to those who do not utilize online resources (Riahi, 2017). By seeking health information online, individuals can gain a better understanding of their health status, which in turn can lead to the formation of informed opinions, beliefs, and attitudes towards healthy behaviors, ultimately aiding in making informed decisions regarding healthcare (Ahedzadeh and Sharif, 2017; Brown, Skelly, Chew-Graham, 2020). Therefore, the objective of this study is to explore the health information-seeking behavior of clients within health and treatment networks in Ahvaz city.
Methods and Materoal
The current research is an experimental study conducted using the pre-test and post-test intervention method. The research population consisted of 40 clients from Ahvaz Medical Center, whose average score of health information-seeking behavior was one point below the average. Of these, 20 individuals were randomly assigned to the control group. Additionally, two groups of 20 people each were formed using block randomization: one as the control group and the other as the test group for the intervention. The educational intervention took the form of a 4-hour online training workshop. To assess changes in online health information search behaviors, uncertainty, and cyberchondria in the study group, the Generalized Estimating Equations (GEE) method was utilized. The protocol used for online education on social networks was the SDI protocol (Bhushan 2006, Juyani et al. 2022). A questionnaire served as the data collection tool, completed by the test groups within one month and returned to the researchers. Data collection occurred at baseline (pre-intervention) and at one, two, and three months post-intervention. Baseline scores were used as covariates in the model to adjust for differences between the control and intervention groups. The results of the GEE model reflected changes in the desired factors at the three measurement points post-intervention. Furthermore, Bonferroni's post hoc test was employed to compare the distribution of online health information search scores, uncertainty, and cyberchondria between the two groups at each time point. All analyses were conducted using SPSS software version 26.
Resultss and Discussion
Findings: There was no significant difference in the effect of the educational intervention on changes in the online health information search score (P>0.05). For the control group, the average uncertainty score increased over time. However, there was a significant difference in the effect of the educational intervention on changes in the uncertainty score (P<0.001). Results of the external post-hoc test comparing changes in the uncertainty score between the two intervention groups and the control group showed a significant difference in the distribution of uncertainty scores before the intervention (P>0.046), as well as two and three months after the intervention (P>0.001). Additionally, there was a significant difference in the cyberchondria score before the intervention (P>0.076) and three months after the intervention (P>0.025) in each case.
Conclusion
Health information behavior training is a positive step towards increasing the decision-making self-efficacy of community members and patients. When combined with other efforts to promote health and care, it can lead to improved health outcomes. The effectiveness of educational interventions in different groups depends on the methods, materials, and content used. This study found that a patient educational intervention aimed at teaching information-seeking behavior skills to health center visitors had a positive impact on reducing cyberchondria and increasing certainty. The availability of information search platforms, the type of sources used, and the ability to utilize them based on age requirements are important factors in information seeking (Bahadir and Dundar, 2022). Uncertainty and doubt can drive individuals to seek health information online (Khademizadeh, Rafieinasab and Radhakrishnan, 2024), making educational interventions focused on empowerment dimensions beneficial in improving clinical and psychological outcomes. These interventions can enhance quality of life for both society and patients, taking into account factors such as age, education, occupation, and income status. This research presents a new approach to educational interventions that are cost-effective, accessible, and complication-free for health management and promotion in society.
With the emergence of the Internet and the expansion of information technologies in the current era, along with the increase in awareness and literacy levels in human societies, there has been a growing interest in accessing information in various fields. One type of information that has always captivated the general public is health-related information, as it directly impacts their quality of life. Health information encompasses a wide range of data that can influence decisions related to individual and social well-being. Electronic health resources play a crucial role in helping individuals manage important health issues, make informed decisions about their health, and communicate with healthcare providers. Studies have shown that internet users not only exhibit better adherence to treatment, reduced anxiety, and a greater sense of security, but also demonstrate improved self-care behaviors compared to those who do not utilize online resources (Riahi, 2017). By seeking health information online, individuals can gain a better understanding of their health status, which in turn can lead to the formation of informed opinions, beliefs, and attitudes towards healthy behaviors, ultimately aiding in making informed decisions regarding healthcare (Ahedzadeh and Sharif, 2017; Brown, Skelly, Chew-Graham, 2020). Therefore, the objective of this study is to explore the health information-seeking behavior of clients within health and treatment networks in Ahvaz city.
Methods and Materoal
The current research is an experimental study conducted using the pre-test and post-test intervention method. The research population consisted of 40 clients from Ahvaz Medical Center, whose average score of health information-seeking behavior was one point below the average. Of these, 20 individuals were randomly assigned to the control group. Additionally, two groups of 20 people each were formed using block randomization: one as the control group and the other as the test group for the intervention. The educational intervention took the form of a 4-hour online training workshop. To assess changes in online health information search behaviors, uncertainty, and cyberchondria in the study group, the Generalized Estimating Equations (GEE) method was utilized. The protocol used for online education on social networks was the SDI protocol (Bhushan 2006, Juyani et al. 2022). A questionnaire served as the data collection tool, completed by the test groups within one month and returned to the researchers. Data collection occurred at baseline (pre-intervention) and at one, two, and three months post-intervention. Baseline scores were used as covariates in the model to adjust for differences between the control and intervention groups. The results of the GEE model reflected changes in the desired factors at the three measurement points post-intervention. Furthermore, Bonferroni's post hoc test was employed to compare the distribution of online health information search scores, uncertainty, and cyberchondria between the two groups at each time point. All analyses were conducted using SPSS software version 26.
Resultss and Discussion
Findings: There was no significant difference in the effect of the educational intervention on changes in the online health information search score (P>0.05). For the control group, the average uncertainty score increased over time. However, there was a significant difference in the effect of the educational intervention on changes in the uncertainty score (P<0.001). Results of the external post-hoc test comparing changes in the uncertainty score between the two intervention groups and the control group showed a significant difference in the distribution of uncertainty scores before the intervention (P>0.046), as well as two and three months after the intervention (P>0.001). Additionally, there was a significant difference in the cyberchondria score before the intervention (P>0.076) and three months after the intervention (P>0.025) in each case.
Conclusion
Health information behavior training is a positive step towards increasing the decision-making self-efficacy of community members and patients. When combined with other efforts to promote health and care, it can lead to improved health outcomes. The effectiveness of educational interventions in different groups depends on the methods, materials, and content used. This study found that a patient educational intervention aimed at teaching information-seeking behavior skills to health center visitors had a positive impact on reducing cyberchondria and increasing certainty. The availability of information search platforms, the type of sources used, and the ability to utilize them based on age requirements are important factors in information seeking (Bahadir and Dundar, 2022). Uncertainty and doubt can drive individuals to seek health information online (Khademizadeh, Rafieinasab and Radhakrishnan, 2024), making educational interventions focused on empowerment dimensions beneficial in improving clinical and psychological outcomes. These interventions can enhance quality of life for both society and patients, taking into account factors such as age, education, occupation, and income status. This research presents a new approach to educational interventions that are cost-effective, accessible, and complication-free for health management and promotion in society.
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